code: def __extract_all_files(filepath: str, data_root: str, data_dir: str):
      if not os.path.exists(data_dir):
          extract_file(filepath, data_root)
          audio_dir = os.path.join(data_dir, "wav")
          for subfolder, _, filelist in os.walk(audio_dir):
              for ftar in filelist:
                  extract_file(os.path.join(subfolder, ftar), subfolder)
      else:
          logging.info(
              "Skipping extracting. Data already there %s" % data_dir
          )
  
file_path: NeMo/scripts/dataset_processing/speaker_tasks/get_hi-mia_data.py
imports: import argparse
  import json
  import logging
  import os
  import tarfile
  import urllib.request
  from glob import glob
  import librosa
  from sklearn.model_selection import StratifiedShuffleSplit
  from tqdm import tqdm
label_desc: Use image node_id 3 for calling a global function with example usage: __extract_all_files(filepath, data_root, data_dir) without return types